56383TVWieckiKRiedingerAAmeln-MayerhoferWJSchmidtMJFrank2009-01-002204265277PsychopharmacologyRationale Repeated haloperidol treatment in rodents results in a day-to-day intensification of catalepsy (i.e., sensitization). Prior experiments suggest that this sensitization is context-dependent and resistant to extinction training.
Objectives The aim of this study was to provide a neurobiological mechanistic explanation for these findings.
Materials and methods We use a neurocomputational model of the basal ganglia and simulate two alternative models based on the reward prediction error and novelty hypotheses of dopamine function. We also conducted a behavioral rat experiment to adjudicate between these models. Twenty male SpragueDawley rats were challenged with 0.25 mg/kg haloperidol across multiple days and were subsequently tested in either a familiar or novel context.
Results Simulation results show that catalepsy sensitization, and its context dependency, can be explained by NoGo learning via simulated D2 receptor antagonism in striatopallidal neurons, leading to increasingly slowed response latencies. The model further exhibits a non-extinguishable component of catalepsy sensitization due to latent NoGo representations that are prevented from being expressed, and therefore from being unlearned, during extinction. In the rat experiment, context dependency effects were not dependent on the novelty of the context, ruling out the novelty models account of context dependency.
Conclusions Simulations lend insight into potential complex mechanisms leading to context-dependent catalepsy sensitization, extinction, and renewal.nonotspecifiedhttp://www.kyb.tuebingen.mpg.de//fileadmin/user_upload/files/publications/Psychopharmacology-Wiecki-preprint_[0].pdfpublished12A neurocomputational account of catalepsy sensitization induced by D2 receptor blockade in rats: context dependency, extinction, and renewal150171882350183KDrewingTVWieckiMOErnst2008-06-002128264273Acta PsychologicaWhen integrating estimates from redundant sensory signals, humans seem to weight these estimates according to their reliabilities. In the present study, human observers used active touch to judge the curvature of a shape. The curvature was specified by positional and force signals: When a finger slides across a surface, the fingers position follows the surface geometry (position signal). At the same time it is exposed to patterns of forces depending on the gradient of the surface (force signal; Robles-de-la Torre &amp;amp; Hayward, 2001). We show that variations in the surfaces material properties (compliance, friction) influence the sensorily available position and force signals, as well as the the noise associated with these signals. Along with this, material properties affect the weights given to the position and force signals for curvature judgements. Our findings are consistent with the notion of an observer who weights signal estimates according to their reliabilities. That is, signal
wei
ghts shifted with the signal noise, which in the present case resulted from active exploration.nonotspecifiedhttp://www.kyb.tuebingen.mpg.de/published9Material Properties Determine How Force and Position Signals Combine in Haptic Shape Perception150171882443047MBethgeTVWieckiFAWichmannSan Jose, CA, USA2007-02-00112SPIE Human Vision and Electronic Imaging Conference 2007The independent components of natural images are a set of linear filters which are optimized for statistical independence. With such a set of filters images can be represented without loss of information. Intriguingly, the filter shapes are localized, oriented, and bandpass, resembling important properties of V1 simple cell receptive fields. Here we address the question of whether the independent components of natural images are also perceptually less dependent than other image components. We compared the pixel basis, the ICA basis and the discrete cosine basis by asking subjects to interactively predict missing pixels (for the pixel basis) or to predict the coefficients of ICA and DCT basis functions in patches of natural images. Like Kersten (1987) we find the pixel basis to be perceptually highly redundant but perhaps surprisingly, the ICA basis showed significantly higher perceptual dependencies than the DCT basis. This shows a dissociation between statistical and perceptual dependence measures.nonotspecifiedhttp://www.kyb.tuebingen.mpg.de//fileadmin/user_upload/files/publications/EI105-IndependentComponents_4304[0].pdfpublished11The Independent Components of Natural Images are Perceptually Dependent1501715420150171882337847KDrewingMOErnstTWieckiPisa, Italy2005-03-00161st Joint Worldhaptic Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (WorldHaptics 2005)When sliding a finger across a bumpy surface, the finger follows the surface geometry (position signal). At the same time the finger is exposed to forces related to the slope of the surface (force signal) [1]. For haptic shape perception the brain uses both signals integrating them by weighted averaging [2]. This is consistent with the Maximum-Likelihood-Estimate (MLE) model on signal integration, previously only applied to passive perception.
The model further predicts that signal weight is proportional to signal reliability. Here, we tested this prediction for the integration of force and position signals to perceived curvature by manipulating material properties of the curve. Low as compared to high compliance decreased the reliability and so the weight of the sensorily transduced position signal. High as compared to low friction decreased the reliability and so the weight of the transduced force signal. These results demonstrat that the MLE model extends to situations involving active touch.nonotspecifiedhttp://www.kyb.tuebingen.mpg.de/fileadmin/user_upload/files/publications/WHC-2005-Drewing.pdfpublished5Material Properties Determine How we Integrate Shape Signals in Active Touch15017154221501718824GerhardWWB20117HEGerhardTWieckiFWichmannMBethgeGöttingen, Germany2011-03-009th Göttingen Meeting of the German Neuroscience Society, 33rd Göttingen Neurobiology ConferenceA long standing hypothesis is that neural representations are adapted to environmental statistical regularities
(Attneave 1954, Barlow 1959), yet the relation between the primate visual system’s functional properties and the
statistical structure of natural images is still unknown. The central problem is that the high-dimensional space of
natural images is difficult to model. While many statistical models of small image patches that have been
suggested share certain neural response properties with the visual system (Atick 1990, Olshausen&Field 1996,
Schwarz&Simoncelli 2001), it is unclear how informative they are about the functional properties of visual
perception. Previously, we quantitatively evaluated how different models capture natural image statistics using
average log-loss (e.g. Eichhorn et al, 2009). Here we assess human sensitivity to natural image structure by
measuring how discriminable images synthesized by statistical models are from natural images. Our goal is to
improve the quantitative description of human sensitivity to natural image regularities and evaluate various
models’ relative efficacy in capturing perceptually relevant image structure.
Methods
We measured human perceptual thresholds to detect statistical deviations from natural images. The task was two
alternative forced choice with feedback. On a trial, two textures were presented side-by-side for 3 seconds: one a
tiling of image patches from the van Hateren photograph database, the other of model-synthesized images (Figure
1A). The task was to select the natural image texture.
We measured sensitivity at 3 patch sizes (3x3, 4x4, & 5x5 pixels) for 7 models. Five were natural image models: a
random filter model capturing only 2nd order pixel correlations (RND), the independent component analysis model
(ICA), a spherically symmetric model (L2S), the Lp-spherical model (LpS), and the mixture of elliptically
contoured distributions (MEC) with cluster number varied at 4 levels (k = 2, 4, 8, & 16). For MEC, we also used
patch size 8x8. We also tested perceptual sensitivity to independent phase scrambling in the Fourier basis (IPS)
and to global phase scrambling (GPS) which preserves all correlations between the phases and between the
amplitudes but destroys statistical dependences between phases and amplitudes. For each type, we presented 30
different textures to 15 naïve subjects (1020 trials/subject).
Results
Figure 1B shows performance by patch size for each model. Low values indicate better model performance as the
synthesized texture was harder to discriminate from natural. Surprisingly, subjects were significantly above chance
in all cases except at patch size 3x3 for MEC. This shows that human observers are highly sensitive to local
higher-order correlations as the models insufficiently reproduced natural image statistics for the visual system.
Further, the psychometric functions’ ordering parallels nicely the models’ average log-loss ordering, beautifully so
within MEC depending on cluster number, suggesting that the human visual system may have near perfect
knowledge of natural image statistical regularities and that average log-loss is a useful model comparison measure
in terms of perceptual relevance. Next, we will determine the features human observers use to discriminate the
textures’ naturalness which can help improve statistical modeling of perceptually relevant natural image structure.nonotspecifiedhttp://www.kyb.tuebingen.mpg.de/published0Perceptual Sensitivity to Statistical Regularities in Natural Images1501718823150171542025157KDrewingTWieckiMOErnstTübingen, Germany2004-02-001237th Tübingen Perception Conference (TWK 2004)When sliding a nger across a bumpy surface, the nger follows the geometry of the bumps/holes
providing positional cues for the shape. At the same time the nger is opposed by forces related
to the steepness of the bumps/holes. With a specic device Robles-de-la-Torre and Hayward [1]
dissociated positional and force cues in the haptic perception of small-scale bumps and holes:
Participants in this experiment reported to predominantly feel the class of shapes (bumps or
holes) indicated by the force cues. Drewing and Ernst [2] extended this research by disentangling
force and position cues to the perception of curves more systematically and by also
quantifying the perceived curvature. The result was that the perceived curvature could be predicted
from weighted averaging of the two cues. This is consistent with current models of cue
integration [e.g., 3].
These integration models further predict that the cue weight is proportional to the cue's
reliability. Here, we aimed at testing this prediction for the integration of force and position
cues to haptic shape by manipulating the shapes' material properties: high softness can be
assumed to decrease the reliability of the position cue as compared to low softness, and high
friction to decrease the reliability of the force cue. Using the PHANToM force-feedback device
we constructed haptic curve stimuli. We systematically intermixed force and position cues
indicating curvatures of 14 and 24 /m. Using the method of double-staircases, we measured
the point of subjective equality (PSE) of the curvature of these as compared to `natural' stimuli
(i.e., with consistent position and force cues). From the PSE data we determined the cue
weights. This was done under each combination of material properties (low vs high softness X
low vs high friction). We found that material properties affected the cue weights in a manner
consistent with our predictions. These results further conrm the validity of existing models of
cue integration in haptic shape perception.nonotspecifiedhttp://www.kyb.tuebingen.mpg.de/published-123Cue Reliabilities Affect Cue Integration in Haptic Shape Perception15017154221501718824